Machine Learning and Big Data with KDB+/Q (Hardcover)
暫譯: KDB+/Q 的機器學習與大數據 (精裝版)

Jan Novotny, Paul A. Bilokon, Aris Galiotos, Frederic Deleze

  • 出版商: Wiley
  • 出版日期: 2019-12-31
  • 定價: $2,500
  • 售價: 9.0$2,250
  • 語言: 英文
  • 頁數: 640
  • ISBN: 1119404754
  • ISBN-13: 9781119404750
  • 相關分類: 大數據 Big-dataMachine Learning
  • 立即出貨 (庫存=1)

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商品描述

Upgrade your programming language to more effectively handle high-frequency data

Machine Learning and Big Data with KDB+/Q offers quants, programmers and algorithmic traders a practical entry into the powerful but non-intuitive kdb+ database and q programming language. Ideally designed to handle the speed and volume of high-frequency financial data at sell- and buy-side institutions, these tools have become the de facto standard; this book provides the foundational knowledge practitioners need to work effectively with this rapidly-evolving approach to analytical trading.

The discussion follows the natural progression of working strategy development to allow hands-on learning in a familiar sphere, illustrating the contrast of efficiency and capability between the q language and other programming approaches. Rather than an all-encompassing “bible”-type reference, this book is designed with a focus on real-world practicality ­to help you quickly get up to speed and become productive with the language.

  • Understand why kdb+/q is the ideal solution for high-frequency data
  • Delve into “meat” of q programming to solve practical economic problems
  • Perform everyday operations including basic regressions, cointegration, volatility estimation, modelling and more
  • Learn advanced techniques from market impact and microstructure analyses to machine learning techniques including neural networks

The kdb+ database and its underlying programming language q offer unprecedented speed and capability. As trading algorithms and financial models grow ever more complex against the markets they seek to predict, they encompass an ever-larger swath of data ­– more variables, more metrics, more responsiveness and altogether more “moving parts.”

Traditional programming languages are increasingly failing to accommodate the growing speed and volume of data, and lack the necessary flexibility that cutting-edge financial modelling demands. Machine Learning and Big Data with KDB+/Q opens up the technology and flattens the learning curve to help you quickly adopt a more effective set of tools.   

商品描述(中文翻譯)

升級您的程式語言以更有效地處理高頻數據

使用 KDB+/Q 的機器學習與大數據 為量化分析師、程式設計師和算法交易者提供了一個實用的入門指南,進入強大但不直觀的 kdb+ 數據庫和 q 程式語言。這些工具理想地設計用來處理賣方和買方機構的高頻金融數據的速度和容量,已成為事實上的標準;本書提供了從業者有效使用這種快速發展的分析交易方法所需的基礎知識。

討論遵循策略開發的自然進程,允許在熟悉的領域中進行實踐學習,展示 q 語言與其他程式設計方法之間的效率和能力對比。本書並非一部包羅萬象的“聖經”式參考書,而是專注於現實世界的實用性,幫助您快速上手並提高使用該語言的生產力。


  • 了解為什麼 kdb+/q 是高頻數據的理想解決方案

  • 深入探討 q 程式設計的“核心”,以解決實際經濟問題

  • 執行日常操作,包括基本回歸、協整、波動性估計、建模等


  • 學習從市場影響和微觀結構分析到機器學習技術(包括神經網絡)的高級技術

kdb+ 數據庫及其底層程式語言 q 提供了前所未有的速度和能力。隨著交易算法和金融模型在試圖預測的市場中變得越來越複雜,它們涵蓋了越來越多的數據——更多的變數、更多的指標、更多的反應性,以及更多的“運動部件”。

傳統程式語言越來越無法滿足不斷增長的數據速度和容量,並缺乏尖端金融建模所需的靈活性。使用 KDB+/Q 的機器學習與大數據 開啟了這項技術,並平坦了學習曲線,幫助您快速採用更有效的工具組。